Computerized tomographic colonography (CTC), a revolutionary new tool, employs specialized imaging software to produce two- and three-dimensional images that permit a thorough and minimally invasive evaluation of the entire colorectum. This nascent imaging tool holds promise in screening colorectal neoplasia based on observations in predominantly high prevalence populations. Unlike conventional endoscopic or radiographic approaches, CTC may allow structural colorectal screening without the discomfort, inconvenience, and risks of a cathartic preparation. This revolutionary approach to full structural examinations exploits the unique capability of CTC, and holds great promise to improve patient compliance by eliminating the disincentive of cathartic preparation-a major obstacle to widespread screening. Data indicates that optimal labeling of stool with a widely acceptable oral contrast agent is feasible, and that detection of colorectal neoplasia is possible. Given the societal importance of colorectal cancer control and the limitations of currently used screening approaches, there exists a strong rationale to aggressively investigate CTC in the unprepared colon for a screening application. It is our objective to improve the performance of CTC in the prepared colon, and to validate CTC in the unprepared colon for the detection of colorectal neoplasia. The proposal addresses aspects of central importance to the clinical application of CTC in two inter-related but independent parts that will be conducted in series. In Part I, methods for optimizing both prepared and unprepared CTC examinations will be explored. Optimization of the prepared colon will be conducted within the context of a screening population. Methods to optimally subtract stool electronically and to detect lesions using computerized intelligence will be explored. In Part 11, the combined clinical performance of CTC in the unprepared colon will be prospectively compared in blinded fashion to colonoscopy. Patient acceptance for each examination, as well as the cost-effectiveness implications of observed performance outcomes, will be evaluated using a predictive model. The study design is fiscally responsible and capitalizes on the abundant clinical and laboratory resources within the Mayo Medical Center. Data generated should provide for a balanced appraisal of the value and practicality of this revolutionary and potentially powerful unique screening tool.